المؤلفون: Fares Azzam, Thomas Blaise, Benjamin Brigaud

المصدر: Sedimentologika, Vol 2, Iss 2 (2024)

مصطلحات موضوعية: Petrographic analysis, Textural analysis, Grain detection, Machine learning, Image segmentation, Geology, QE1-996.5

وصف الملف: electronic resource

Relation: https://oap.unige.ch/journals/sdk/article/view/1594; https://doaj.org/toc/2813-415X

URL الوصول: https://doaj.org/article/ed52c4e4d5154eddbc0878e60ac056e2

المؤلفون: Ruoling Deng, Weilin Cheng, Haitao Liu, Donglin Hou, Xiecheng Zhong, Zijian Huang, Bingfeng Xie, Ningxia Yin

المصدر: Agriculture, Vol 14, Iss 7, p 1135 (2024)

مصطلحات موضوعية: grain number, rice whole panicle, grain detection, convolutional neural network, plant phenotyping, Agriculture (General), S1-972

وصف الملف: electronic resource

Relation: https://www.mdpi.com/2077-0472/14/7/1135; https://doaj.org/toc/2077-0472

URL الوصول: https://doaj.org/article/7acd170011c34d9fa6436e455d8e676b

المؤلفون: Azzam, Fares, Blaise, Thomas, Brigaud, Benjamin

المصدر: Sedimentologika; Vol. 2 No. 2 (2024) ; 2813-415X

مصطلحات موضوعية: Petrographic analysis, Textural analysis, Grain detection, Machine learning, Image segmentation

وصف الملف: application/pdf

Relation: https://oap.unige.ch/journals/sdk/article/view/1594/1567; https://oap.unige.ch/journals/sdk/article/view/1594

الاتاحة: https://oap.unige.ch/journals/sdk/article/view/1594

المؤلفون: Hongle WANG, Xinglin WANG, Wenbo LI, Apei ZOU, Quanzhou YE, Dacun LIU

المصدر: Guangdong nongye kexue, Vol 49, Iss 12, Pp 143-150 (2022)

مصطلحات موضوعية: rice, grain detection, oriented bounding box, aspect ratio, object detection, computer vision, Agriculture

وصف الملف: electronic resource

Relation: http://gdnykx.cnjournals.org/gdnykx/ch/reader/view_abstract.aspx?file_no=202212016; https://doaj.org/toc/1004-874X

URL الوصول: https://doaj.org/article/f3daa38d0dd7462a8cd110d0e573e790

المؤلفون: Yu Zou, Zefeng Tian, Jiawen Cao, Yi Ren, Yaping Zhang, Lu Liu, Peijiang Zhang, Jinlong Ni

المصدر: Sensors, Vol 23, Iss 22, p 9129 (2023)

مصطلحات موضوعية: rice grain detection and counting, YOLOv5, coordinate attention module, transform, Chemical technology, TP1-1185

وصف الملف: electronic resource

Relation: https://www.mdpi.com/1424-8220/23/22/9129; https://doaj.org/toc/1424-8220

URL الوصول: https://doaj.org/article/14f73c50d85249dd8c8cfcb833c84896

المؤلفون: Mingchun Li, Dali Chen, Shixin Liu

المصدر: IEEE Access, Vol 8, Pp 135640-135651 (2020)

مصطلحات موضوعية: Grain detection, boundary detection, generative adversarial network, semi-supervised learning, transfer learning, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/9146826/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/0411fe10b23142a2aa1413d1c39e54b8

المؤلفون: Ruoling Deng, Ming Tao, Xunan Huang, Kemoh Bangura, Qian Jiang, Yu Jiang, Long Qi

المصدر: Sensors; Volume 21; Issue 1; Pages: 281

مصطلحات موضوعية: grain detection, primary branch, convolutional neural network, image, rice

وصف الملف: application/pdf

Relation: Sensing and Imaging; https://dx.doi.org/10.3390/s21010281

الاتاحة: https://doi.org/10.3390/s21010281

المؤلفون: Hao, Feng, Daolin, Guo, Peng, Xie, Xuemei, Jiang, Xiaojun, Zhao

المصدر: Julius-Kühn-Archiv, Vol 463, Iss 1, Pp 288-292 (2018)

مصطلحات موضوعية: grain detection system, industry 4.0, the integration of equipment, Agriculture, Botany, QK1-989

وصف الملف: electronic resource

Relation: https://www.openagrar.de/receive/openagrar_mods_00078178; https://doaj.org/toc/1868-9892; https://doaj.org/toc/2199-921X

URL الوصول: https://doaj.org/article/aaf23850acdd4f6a9eceb048c50c7ffd

المؤلفون: Budzan, Sebastian, Buchczik, Dariusz, Pawełczyk, Marek, Tůma, Jiří

مصطلحات موضوعية: grain detection, seeded region growing segmentation, edge detection, feature extraction

Relation: Sensors; https://doi.org/10.3390/s19081805; Sensors. 2019, vol. 19, issue 8, art. no. 1805.; http://hdl.handle.net/10084/137550; 000467644500059

الاتاحة: http://hdl.handle.net/10084/137550
https://doi.org/10.3390/s19081805

المؤلفون: Deng Ruoling, Kemoh Bangura, Long Qi, Jiang Qian, Huang Xunan, Tao Ming, Yu Jiang

المصدر: Sensors, Vol 21, Iss 281, p 281 (2021)
Sensors
Volume 21
Issue 1
Sensors (Basel, Switzerland)

مصطلحات موضوعية: 0106 biological sciences, convolutional neural network, lcsh:Chemical technology, 01 natural sciences, Biochemistry, Convolutional neural network, Article, Analytical Chemistry, 03 medical and health sciences, Automation, Deep Learning, lcsh:TP1-1185, Pyramid (image processing), image, Electrical and Electronic Engineering, Instrumentation, 030304 developmental biology, Mathematics, Panicle, 0303 health sciences, Grain moisture, business.industry, Deep learning, rice, Grain number, Oryza, primary branch, Atomic and Molecular Physics, and Optics, grain detection, Plant Breeding, Phenotype, Feature (computer vision), Grain yield, Artificial intelligence, Biological system, business, Edible Grain, 010606 plant biology & botany

وصف الملف: application/pdf

URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b899819eefee0da562b90aba29e94ace
https://www.mdpi.com/1424-8220/21/1/281

المؤلفون: Tsiknakis, Nikos, Savvidaki, Elisavet, Kafetzopoulos, Sotiris, Manikis, Georgios, Vidakis, Nikolas, Marias, Kostas, Alissandrakis, Eleftherios

مصطلحات موضوعية: cretan, melissopalinology, pollen analysis, pollen dataset, pollen grain, pollen grain detection, pollen grain segmentation

Relation: https://doi.org/10.3390/app11146657; https://doi.org/10.5281/zenodo.4756360; https://doi.org/10.5281/zenodo.4756361; oai:zenodo.org:4756361

الاتاحة: https://doi.org/10.5281/zenodo.4756361